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(单词翻译:双击或拖选)
My job at Twitter is to ensure user trust, protect user rights and keep users safe, both from each other and, at times, from themselves. Let's talk about what scale looks like at Twitter. Back in January 2009, we saw more than two million new tweets each day on the platform. January 2014, more than 500 million. We were seeing two million tweets in less than six minutes. That's a 24,900-percent increase.
Now, the vast majority of activity on Twitter puts no one in harm's way. There's no risk involved. My job is to root out and prevent activity that might. Sounds straightforward1, right? You might even think it'd be easy, given that I just said the vast majority of activity on Twitter puts no one in harm's way. Why spend so much time searching for potential calamities2 in innocuous activities? Given the scale that Twitter is at, a one-in-a-million chance happens 500 times a day. It's the same for other companies dealing3 at this sort of scale. For us, edge cases, those rare situations that are unlikely to occur, are more like norms. Say 99.999 percent of tweets pose no risk to anyone. There's no threat involved. Maybe people are documenting travel landmarks4 like Australia's Heart Reef, or tweeting about a concert they're attending, or sharing pictures of cute baby animals. After you take out that 99.999 percent, that tiny percentage of tweets remaining works out to roughly 150,000 per month. The sheer scale of what we're dealing with makes for a challenge.
You know what else makes my role particularly challenging? People do weird5 things. (Laughter) And I have to figure out what they're doing, why, and whether or not there's risk involved, often without much in terms of context or background. I'm going to show you some examples that I've run into during my time at Twitter -- these are all real examples — of situations that at first seemed cut and dried, but the truth of the matter was something altogether different. The details have been changed to protect the innocent and sometimes the guilty. We'll start off easy.
["Yo bitch"]
If you saw a Tweet that only said this, you might think to yourself, "That looks like abuse." After all, why would you want to receive the message, "Yo, bitch." Now, I try to stay relatively6 hip7 to the latest trends and memes, so I knew that "yo, bitch" was also often a common greeting between friends, as well as being a popular "Breaking Bad" reference. I will admit that I did not expect to encounter a fourth use case. It turns out it is also used on Twitter when people are role-playing as dogs. (Laughter) And in fact, in that case, it's not only not abusive, it's technically8 just an accurate greeting. (Laughter)
So okay, determining whether or not something is abusive without context, definitely hard.
Let's look at spam. Here's an example of an account engaged in classic spammer behavior, sending the exact same message to thousands of people. While this is a mockup I put together using my account, we see accounts doing this all the time. Seems pretty straightforward. We should just automatically suspend accounts engaging in this kind of behavior. Turns out there's some exceptions to that rule. Turns out that that message could also be a notification you signed up for that the International Space Station is passing overhead because you wanted to go outside and see if you could see it. You're not going to get that chance if we mistakenly suspend the account thinking it's spam.
Okay. Let's make the stakes higher. Back to my account, again exhibiting classic behavior. This time it's sending the same message and link. This is often indicative of something called phishing, somebody trying to steal another person's account information by directing them to another website. That's pretty clearly not a good thing. We want to, and do, suspend accounts engaging in that kind of behavior. So why are the stakes higher for this? Well, this could also be a bystander at a rally who managed to record a video of a police officer beating a non-violent protester who's trying to let the world know what's happening. We don't want to gamble on potentially silencing that crucial speech by classifying it as spam and suspending it. That means we evaluate hundreds of parameters9 when looking at account behaviors, and even then, we can still get it wrong and have to reevaluate.
Now, given the sorts of challenges I'm up against, it's crucial that I not only predict but also design protections for the unexpected. And that's not just an issue for me, or for Twitter, it's an issue for you. It's an issue for anybody who's building or creating something that you think is going to be amazing and will let people do awesome10 things. So what do I do? I pause and I think, how could all of this go horribly wrong? I visualize11 catastrophe12. And that's hard. There's a sort of inherent cognitive13 dissonance in doing that, like when you're writing your wedding vows14 at the same time as your prenuptial agreement. (Laughter) But you still have to do it, particularly if you're marrying 500 million tweets per day. What do I mean by "visualize catastrophe?" I try to think of how something as benign15 and innocuous as a picture of a cat could lead to death, and what to do to prevent that. Which happens to be my next example. This is my cat, Eli. We wanted to give users the ability to add photos to their tweets. A picture is worth a thousand words. You only get 140 characters. You add a photo to your tweet, look at how much more content you've got now. There's all sorts of great things you can do by adding a photo to a tweet. My job isn't to think of those. It's to think of what could go wrong.
How could this picture lead to my death? Well, here's one possibility. There's more in that picture than just a cat. There's geodata. When you take a picture with your smartphone or digital camera, there's a lot of additional information saved along in that image. In fact, this image also contains the equivalent of this, more specifically, this. Sure, it's not likely that someone's going to try to track me down and do me harm based upon image data associated with a picture I took of my cat, but I start by assuming the worst will happen. That's why, when we launched photos on Twitter, we made the decision to strip that geodata out. (Applause) If I start by assuming the worst and work backwards16, I can make sure that the protections we build work for both expected and unexpected use cases.
Given that I spend my days and nights imagining the worst that could happen, it wouldn't be surprising if my worldview was gloomy. (Laughter) It's not. The vast majority of interactions I see -- and I see a lot, believe me -- are positive, people reaching out to help or to connect or share information with each other. It's just that for those of us dealing with scale, for those of us tasked with keeping people safe, we have to assume the worst will happen, because for us, a one-in-a-million chance is pretty good odds17.
Thank you.
(Applause)
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收听单词发音
收听单词发音 |
1
straightforward
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| adj.正直的，坦率的；易懂的，简单的 | |
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calamities
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| n.灾祸，灾难( calamity的名词复数 )；不幸之事 | |
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dealing
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| n.经商方法，待人态度 | |
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landmarks
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| n.陆标( landmark的名词复数 )；目标；（标志重要阶段的）里程碑 ~ (in sth)；有历史意义的建筑物（或遗址） | |
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weird
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| adj.古怪的，离奇的；怪诞的，神秘而可怕的 | |
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relatively
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| adv.比较...地，相对地 | |
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hip
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| n.臀部，髋；屋脊 | |
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technically
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| adv.专门地，技术上地 | |
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9
parameters
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| 因素，特征； 界限； （限定性的）因素( parameter的名词复数 )； 参量； 参项； 决定因素 | |
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10
awesome
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| adj.令人惊叹的，难得吓人的，很好的 | |
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visualize
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| vt.使看得见，使具体化，想象，设想 | |
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catastrophe
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| n.大灾难，大祸 | |
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cognitive
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| adj.认知的，认识的，有感知的 | |
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14
vows
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| 誓言( vow的名词复数 )； 郑重宣布，许愿 | |
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benign
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| adj.善良的，慈祥的；良性的，无危险的 | |
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16
backwards
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| adv.往回地，向原处，倒，相反，前后倒置地 | |
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odds
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| n.让步，机率，可能性，比率；胜败优劣之别 | |
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